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Deploy Folder To Modelscope

Checked
cafe3310·vlatest·devops·Apache-2.0

Uploads a specified folder of files to a designated ModelScope repository using cafe3310's deployment tool.

Repository

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

  1. 1

    Run this in your project

    terminal
    $ npx skills add cafe3310/public-agent-skills --skill deploy-folder-to-modelscope --full-depth -a claude-code

  2. Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

cafe3310

Taken from the source listing. We haven't verified who controls this account.

Install target

Live repository

Not pinned. Installing fetches whatever the repository holds at the time you run the command.

No human has reviewed this code. The checks below are a static scan of the files at one commit — nobody has run this skill or judged whether it works. A skill runs with whatever access you give your agent, so read the source before you install it.

Automated safety checks

scanned

This skill passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.

  • Declares what it does: passed

    SKILL.md parses and declares a name and a description.

    SKILL.md exists, its frontmatter parses, and it declares a name and a description.

  • No undeclared network calls: passed

    Makes no network calls.

    Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.

  • No obfuscated payloads: passed

    No encoded or obfuscated payloads.

    No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.

  • No credential access: passed

    Reads no keys, tokens, keychains or credential files.

    Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.

  • No pipe-to-shell installers: passed

    No pipe-to-shell or download-and-run installers.

    No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.

  • Pinned to a commit: passed

    Scanned cafe3310/public-agent-skills at 6c4550158f.

    The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.

Commit
6c4550158f
Manifest
skills_parked/deploy-folder-to-modelscope/SKILL.md
Scanned
3 files, 276 lines
This is a static scan, not a review. It reads the skill's files; it does not run them, and it cannot tell you whether the skill is any good or whether the code does what its description says. A skill runs with whatever access you give your agent.
What each check looks for →

About this skill

What it does

This skill allows an AI agent to deploy a folder of files directly to a ModelScope repository. It automates the process of uploading data and models, simplifying the deployment workflow for machine learning projects. The skill handles file organization and uploads, making it easier to share and utilize your work within the ModelScope ecosystem.

When to use it

  • You've trained a model and want to quickly make its dataset and code available on ModelScope.
  • You need to regularly update a ModelScope repository with new data or model versions.
  • You’re collaborating with others and want a standardized way to share your machine learning project files.
  • You are automating the deployment of a research project to ModelScope for reproducibility.

Key capabilities

  • Folder upload to ModelScope repositories
  • Automated file organization during deployment
  • Simplified model sharing on ModelScope

Example prompts

  • "Deploy the 'my_project' folder to my ModelScope repository."
  • "Upload all files in the 'data' directory to my ModelScope account."
  • “Can you deploy this project to ModelScope?”

Tips & gotchas

  • Ensure you have appropriate credentials and permissions configured for accessing your ModelScope account. The skill requires access to a valid ModelScope repository.